Fully Automated Detection Robot Promotes Efficient Soil Testing

May 15, 2024 | By CHEN Xiangyu; ZHAO Weiwei

A research team led by Professor WANG Rujing from Hefei Institutes of Physical Science of Chinese Academy of Sciences developed a new equipment which achieved fully automated and unmanned detection soil nutrients (such as Organic Matter, Available Potassium, Available Phosphorus) and heavy metals (including Pb, Cd, Hg, As, Cr). They named it the High Throughput Soil Composition Intelligent Detection Robot Equipment.

Cultivated land is essential for food production. To address the challenges of lengthy cycles, intricate procedures, and high costs associated with large-scale manual soil testing, advanced technological solutions are required.

This equipment has three technological highlights: machine vision, multi-arm coordination, and optimized scheduling algorithms.

Machine vision identifies colors in chemical titration reactions. The team uses a camera to capture images, digitizes them, and matches RGB color components to determine the threshold of color changes in the reactions.

Multi-arm coordination uses neural networks and distributed control to break down complex actions into precise mechanical arm movements. This enables efficient planning, decision-making, and coordinated control of multiple arms, ensuring accurate and efficient pre-treatment actions.

The optimized scheduling algorithm uses a cloud-based laboratory management platform to coordinate sampling, weighing, pre-treatment, and testing for various indicators like pH and available potassium. It ensures accuracy and prioritizes efficiency, enabling the efficient operation of the soil sample pre-treatment process.

By replacing complex manual labor with robots, this equipment enhances the efficiency and accuracy of soil testing, according to the team.

High Throughput Soil Composition Intelligent Detection Robot Equipment (Image by HFIPS)

The equipment realized fully automated and unmanned detection of soil nutrients and heavy metals. (Image by HFIPS)

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